Build Movie Review Classification with BERT and Tensorflow

About this course

Learn to build Moview Review Classifier engine with BERT and TensorFlow 2.4Build a strong foundation in Deep learning text classifiers with this tutorial for beginners.

Understanding of movie review classification Learn word embeddings from scratch

Learn BERT and its advantages over other technologies

Leverage pre-trained model and fine-tune it for the questions classification task

Learn how to evaluate the model

User Jupyter Notebook for programming

Test model on real-world dataA Powerful Skill at Your Fingertips Learning the fundamentals of text classification h puts a powerful and very useful tool at your fingertips. Python and Jupyter are free, easy to learn, have excellent documentation. Text classification is a fundamental task in the natural language processing (NLP) world.

No prior knowledge of word embedding or BERT is assumed. I'll be covering topics like Word Embeddings, BERT, and Glove from scratch. Jobs in the NLP area are plentiful, and being able to learn text classification with BERT will give you a strong edge. BERT is state of art language model and surpasses all prior techniques in natural language processing. Google uses BERT for text classification systems. Text classifications are vital in social media. Learning text classification with BERT and Tensorflow 2.4 will help you become a natural language processing (NLP) developer which is in high demand.

Content and Overview This course teaches you how to build a movie review classification engine using open-source Python, Tensorflow 2.4, and Jupyter framework. You will work along with me step by step to build a movie review classification engine Word Embeddings

• Word2Vec
• One hot encoding
• Glov

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